Observability is an end-to-end framework for collecting telemetry data, such as logs, traces, metrics, events, etc., at both the infrastructure and application levels, then processing, analyzing, and visualizing that information to find issues and understand why they occur.
To make a system observable, you need telemetry data from all system components consisting mainly of logs, traces, and metrics.
There are many open-source and vendor-provided observability tools. Below are some of the open-source observability tools.
Nowadays, it’s common for companies to have distributed systems. All observability data should be in one stack to monitor these systems and gain insights effectively, which Elastic Observability (built on the popular ELK stack) makes possible. By bringing the application, infrastructure, and user data into a unified solution, silos converge.
Key features of Elastic Observability:
OpenTelemetry (OTEL) is an open-source observability framework sponsored by the CNCF (Cloud Native Computing Foundation) that was formed by merging the OpenTracing and OpenCensus projects. OpenTelemetry does not provide an observable back-end. It’s up to the Ops team to export data to one of the many available analytical tools. OpenTelemetry helps developers and Ops teams by providing pluggable architecture so that formats and additional protocols can be added easily.
The components of OpenTelemetry are listed below:
Key features of OpenTelemetry:
Apache Skywalking is one of the most popular open-source tools to provide both Application Performance Monitoring (APM) and Observability capabilities. It is designed for distributed systems, microservices, cloud-native and container-based or Kubernetes architectures. It supports the three pillars of observability (Logs, Metrics, and Traces) by collecting data from multiple sources, formats, and programming languages such as Java, .NET Core, NodeJS, PHP, Python, Golang, C++, etc.
Skywalking OAP (Observability Analysis Platform) uses STAM (the Streaming Topology Analysis Method) to analyze the topology for better performance in the tracing-based agent scenario.
Key features of Skywalking:
inspectIT Ocelot agent is a zero-configuration Java agent that collects application performance, tracing, and business data. It unlocks observability for Java monitoring. The agent uses Java byte-code manipulation to set up the OpenCensus instrumentation library with zero configuration and no changes in source code. inspectIT Ocelot supports multiple exporters for Java such as Prometheus, Zipkin, Jaeger, etc. that OpenCensus offers. It can be integrated with APM tools such as Grafana to get great visualizations and dashboards to visualize the data.
Key Features of inspectIT Ocelot:
Vector is an open-source observability data platform that allows users to collect and transform all the logs, metrics, and traces from on-premises and cloud environments. It then routes them to any open-source or vendor-provided tool and allows users to control how data moves through the pipeline, cost control, and compliance management. In addition, it helps users manage how the telemetry data is ingested, enriched, stored, and routed to build cost-efficient yet fully capable data pipelines in the cloud and on-prem environments. Datadog acquired Timber Technologies, the company behind Vector, in 2021.
Vector has the following components:
Key features of Vector:
SigNoz is an open-source observability tool that provides metrics monitoring and distributed tracing and natively supports OpenTelemetry. In addition, SigNoz provides visualizations for traces and metrics data.
Below are the components of SigNoz:
Key features of SigNoz:
Jaeger is an open-source distributed tracing system developed by Uber, inspired by Dapper and OpenZipkin. It is used for monitoring, and troubleshooting microservices-based distributed systems and provides distributed context propagation, transaction monitoring, service dependency analysis, root cause analysis, and performance or latency optimization.
Jaeger’s components are listed below:
Key features of Jaeger:
Zipkin is an open-source distributed tracing system originally developed by Twitter. Zipkin, at its core, is a Java-based application that provides several services that can collect and look up data from distributed systems. It also gathers the timing data needed to troubleshoot any problems when incidents occur.
Below are the components of Zipkin:
Key Features of Zipkin:
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